Hybrid Reservoir Modeling and Evaluation Merging Physics and Data-Driven Technology

Monday, 23 September

1400 - 1700

Room 220 - 222

Technical Session

This session is focused on integration of advanced machine learning technologies into existing workflows for reservoir modeling and evaluation. Highlights includes using data analytics to analyze large datasets and extract meaningful insights and using hybrid approaches for well performance analysis, completion design, connectivity analysis, and enhancement of reservoir modeling and simulation.

Session Chairpersons

Lei Wang - Parker Drilling Co.

Dingzhou Cao - Devon Energy Corporation

1400-1425 220875
Analyzing Impact Of Fracturing Revolution On Shale Oil Well Performance In Permian Basin: A Review From Over 10,000 Wells

K. Zhang, OGRE Systems; Q. Lu, Sinopec Petroleum Exploration and Production Research Institute; X. Xia, Ryder Scott Company, L.P.; J. Li, Sinopec Petroleum Exploration and Production Research Institute; F. Wang, S. Gao, Sinopec Exploration and Production Department; L. Xu, OGRE Systems,Inc; D. Olds, H. Zhang, Ryder Scott Company, L.P.
1425-1450 220989
A New Algorithm For Automated ISIP Interpretation

A.G. Garbino, D.N. Espinoza, The University of Texas At Austin; A.A. Savitski, S. Mondal, Shell Exploration & Production Co
1450-1515 220933
A Hybrid Approach For Production Forecasting And Uncertainty Characterization

Z. Guo, S. Sankaran, Xecta Digital Labs
1545-1610 220978
Transfer Learning in Subsurface Flow Surrogate Model with Physics-Guided Neural Network

H. Cheng, J. Qiao, Shenyang Institute of Automation, Chinese Academy of Sciences; Y. Wei, Institute for Interdisciplinary Information Sciences, Tsinghua University; S. Li, P. Zeng, H. Yu, Shenyang Institute of Automation, Chinese Academy of Sciences
1610-1635 220906
Application Of Artificial Intelligence To Model Stresses And Failure Parameters In Anisotropic Formations

W. Yousuf, Texas A&M University; J. Kim, Texas A & M U (PE Dept Po's )
1635-1700 221029
Fast Evaluation of Reservoir Connectivity via a New Deep Learning Approach: Attention-based Graph Neural Network for Fusion Model

T.A. Saihood, University of Houston; A.A. Saihood, Thi Qar University; M. Al-Shaher, University of Thi-Qar; C. Ehlig-Economides, Z. Zargar, University of Houston
Alternate 220838
Enhanced 3D Pore Segmentation And Multi-model Pore-scale Simulation By Deep Learning

H. Li, B. Aslam, B. Yan, King Abdullah University of Science & Tech
Alternate 221028
Enhancing Reservoir Model History Matching With Ai Surrogate And Ensemble Iterative Algorithms

K. Hammad, A. Alturki, Saudi Aramco; S. Sudirman, Saudi Aramco PE&D; Z. Sawlan, King Fahd University of Petroleum and Minerals

2024 Technical Program

Hybrid Reservoir Modeling and Evaluation Merging Physics and Data-Driven Technology